Spell checking of text in word processors, spreadsheets, emails, web pages and other computer documents has become common place. Yet, geographic information system (GIS) software products do not include built-in spell checkers. A geographic information system is a system for capturing, integrating, storing, managing, editing, analyzing, sharing and displaying data and associated attributes which are spatially referenced, typically to the earth. One known GIS provider informs its power users on how to plug in a conventional spell checker to check the spelling of text against a conventional dictionary. However, such a solution does not take into consideration map-specific factors that render such a conventional method of spell-checking very ineffective.
One of the reasons for the lack of such spell checkers was the conceptual and technical difficulties related to the spell checking of geographically-bound text in maps. Much of the text in maps is geographically-bound and, as such, has to be spell-checked differently from text in other types of documents. Some map text is geographically-bound because the spelling of a particular word may be valid in one area of the map but may not be valid in another. For example, a city name is valid near the city of that name, but may not be valid elsewhere on the map. Another difficulty in spell-checking maps arises because many of the words on maps are proper nouns, such as geographic names. Alphabetic dictionaries, such as those used in word processors, may contain the spelling of some major geographic features such as countries and major cities but are unlikely going to contain local geographic names. This is for good reason, as there are millions of such local geographic names and most of those spellings are only valid at certain narrow locations.
Yet another difficulty arises because text in maps is typically in the language of the intended reader, in the language or languages of the locale where features (cities, churches, etc.) being labeled lie, or a combination. This makes the spell checking of such maps more challenging.
Furthermore, GIS databases and maps can contain enormous amounts of text. Spell checking and potentially correcting each word at a time, as conventional spell-checkers do, is not practical. Such serial, individual spell-checking wastes the users' time by requiring that they wait for the system to find each error before fixing it manually and proceeding to finding the next error.
In addition, one conventional spell-checker controls what text should be spell checked by requiring that the user first select each individual text object manually. Such a requirement is impractical in most situations.